Optimal sampling design and the accuracy of occupancy models

Designing a surveillance program for early detection of alien plants and insects in Norway

Naturalized species of alien plants and animals comprise < 3% of biodiversity recorded in Norway but have had major impacts on natural ecosystems through displacement of native species. Encroachment of alien species has been especially problematic for coastal sites close to transport facilities and urban areas with high density housing. The goal of our field project was to design and test a surveillance program for early detection of alien species of vascular plants and terrestrial insects at the first phase of establishment in natural areas. In our 3-year project (2018–2020), we sampled 60 study plots in three counties in the Oslofjord region of southern Norway. Study plots (6.25 ha) were selected by two criteria: manual selection based on expert opinion (27 plots) or by random selection based on weights from a hotspot analysis of occurrence of alien species (33 plots). Vascular plants were surveyed by two experienced botanists who found a total of 239 alien species of vascular plants in 95 rounds of surveys. Insects and other invertebrates were captured with a single Malaise trap per site, with 3–4 rounds of repeated sampling. We used DNA-metabarcoding to identify invertebrates based on DNA extractions from crushed insects or from the preservative media. Over 3500 invertebrate taxa were detected in 255 rounds of sampling. We recorded 20 alien species of known risk, and 115 species that were new to Norway, including several ‘doorknocker’ species identified by previous risk assessments. We modeled the probabilities of occupancy (ψ) and detection (p) with occupancy models with repeated visits by multiple observers (vascular plants) or multiple rounds of sampling (insects). The two probabilities covaried with risk category for alien organisms and both were low for species categorized as no known or low risk (range = 0.052–0.326) but were higher for species categorized as severe risk (range = 0.318–0.651). Selecting sites at random or manually did not improve the probability of finding novel alien species, but occupancy had a weak positive relationship with housing density for some categories of alien plants and insects. We used our empirical estimates to test alternative sampling designs that would minimize the combined variance of occupancy and detection (A-optimality criterion). Sampling designs with 8–10 visits per site were best for surveillance of new alien species if the probabilities of occupancy and detection were both low, and provided low conditional probabilities of site occupancy ($$\hat{\psi }_{condl}$$ ψ ^ condl ≤ 0.032) and a high probabilities of cumulative detection ($$\hat{p}*$$ p ^ ∗  ≥ 0.943). Our field results demonstrate that early detection is feasible as a key component of a national surveillance program based on early detection and rapid response.

Time-to-detection occupancy methods: performance and utility for improving efficiency of surveys

Occupancy methods propelled the quantitative study of species distributions forward by separating the observation process, or the imperfect detectability of species, from the ecological processes of interest governing species distributions. Occupancy studies come at a cost, however: the collection of additional data to account for nondetections at sites where the species is present. The most common occupancy designs (repeated-measures designs) require repeat visits to sites or the use of multiple observers or detection methods. Time-to-detection methods have been identified as a potentially efficient alternative, requiring only one visit to each site by a single observer. A comparison of time-to-detection methods to repeated-measures designs for visual encounter surveys would allow researchers to evaluate whether time-to-detection methods might be appropriate for their study system and can inform optimal survey design. We collected time-to-detection data during two different repeated-measures design occupancy surveys for four amphibians and compared the performance of time-to-detection methods to the other designs using the location (potential bias) and precision of posterior distributions for occurrence parameters. We further used results of time-to-detection surveys to optimize survey design. Time-to-detection methods performed best for species that are widespread and have high detection probabilities and rates, but performed less well for cryptic species with lower probability of occurrence or whose detection was strongly affected by survey conditions. In all cases, single surveys were most efficient in terms of person-hours expended, but under some conditions the survey duration required to achieve high detection probabilities would be prohibitively long for a single survey. Regardless of occupancy survey design, time-to-detection methods provide important information that can be used to optimize surveys, allowing researchers and resource managers to efficiently achieve monitoring and conservation goals. Collecting time-to-detection data while conducting repeated-measures occupancy surveys requires only small modifications to field methods but could have large benefits in terms of time spent surveying in the long term.